The present disclosure relates generally to building management systems and associated devices and more particularly to a heating, ventilating, or air conditioning (HVAC) controller device for a building management system (BMS) with automatic configuration and machine learning capabilities.
HVAC control systems are used to monitor and control temperature, humidity, air flow, air quality, and/or other conditions within a building or building system. HVAC control systems typically include a plurality of measurement devices (e.g., temperature sensors, pressure sensors, flow sensors, etc.), control devices (e.g., chillers, boilers, air handling units, variable air volume units, etc.), and a controller for receiving feedback from the measurement devices and providing a control signal to the control devices. Some HVAC control systems include a main controller and one or more auxiliary, or subordinate, controllers.
Current HVAC control systems often use fixed point controllers in which the sensors used to measure environmental properties must be individually defined in a controller file and correctly wired to ensure that the control system is receiving sensor data of the expected type and from the expected location. As a result, the control system is unable to accommodate any sensor devices other than those defined in the controller file. Systems and methods to reduce the complexity of the control system installation process and increase the flexibility of the system to accommodate additional sensor devices would be useful.